Governance and review
Governance and review are crucial aspects of managing LLMs in LLMOps, ensuring that the models are secure, compliant with regulations, and functionally robust. This process involves safeguarding against data leakage, controlling access to information, thorough evaluation of model performance, and adherence to legal standards such as the General Data Protection Regulation (GDPR).
Avoiding training data leakage
When developing and training LLMs, we need to prevent what is known as training data leakage. This term refers to the inadvertent incorporation of sensitive information from the training dataset into the model’s knowledge base, potentially leading to significant privacy breaches. Such breaches not only compromise individual privacy but can also have broader implications for data protection and trust in AI systems.
To combat this, one effective strategy that’s employed is data anonymization. Before the training data is fed into the model...
